Sample size determination in the context of Bayesian analysis {https://t.co/uH1Zv7sKbc} #rstats #DataScience
— R-bloggers (@Rbloggers) June 2, 2021
Tips And Tricks For Data Scientists Vol.8 {https://t.co/90NhaupOPE} #rstats #DataScience
— R-bloggers (@Rbloggers) May 29, 2021
Host Shiny Apps with Docker {https://t.co/VBBJbzvN8u} #rstats #DataScience
— R-bloggers (@Rbloggers) May 31, 2021
ivreg: Two-stage least-squares regression with diagnostics {https://t.co/jWSOvTCoHg} #rstats #DataScience
— R-bloggers (@Rbloggers) May 31, 2021
R for Public Health {https://t.co/7xPFGsZrEK} #rstats #DataScience
— R-bloggers (@Rbloggers) June 3, 2021
Hierarchical forecasting of hospital admissions {https://t.co/D8q0UJhvy3} #rstats #DataScience
— R-bloggers (@Rbloggers) June 4, 2021
Working with files and folders in R-Ultimate Guide {https://t.co/dniolIlkOh} #rstats #DataScience
— R-bloggers (@Rbloggers) May 29, 2021
How to Build Analytics Technical Skills (How to Get an Analytics Job Podcast) {https://t.co/1TnpsPcDKA} #rstats #DataScience
— R-bloggers (@Rbloggers) May 30, 2021
2021-01 Accessing ‘grid’ from ‘ggplot2’ {https://t.co/pBF9Eb2sZY} #rstats #DataScience
— R-bloggers (@Rbloggers) May 31, 2021
summarize in r, Data Summarization In R {https://t.co/gsPowhj5st} #rstats #DataScience
— R-bloggers (@Rbloggers) June 2, 2021
Skewness in Statistics-Calculate Skewness in R {https://t.co/mgcn8jBB8B} #rstats #DataScience
— R-bloggers (@Rbloggers) June 3, 2021
Replace residPlot() with ggplot {https://t.co/rTLq9uLc12} #rstats #DataScience
— R-bloggers (@Rbloggers) June 2, 2021
Shiny UI Breakthrough: Develop Professional Shiny Apps with shiny.fluent {https://t.co/SYwECl4KBJ} #rstats #DataScience
— R-bloggers (@Rbloggers) June 2, 2021
Sentiment analysis in R {https://t.co/HoyxGDHj7J} #rstats #DataScience
— R-bloggers (@Rbloggers) May 16, 2021
Visualization Graphs-ggside with ggplot {https://t.co/kRY5wVY2VN} #rstats #DataScience
— R-bloggers (@Rbloggers) May 12, 2021
Text Analysis with R {https://t.co/Bn4k0cwfhj} #rstats #DataScience
— R-bloggers (@Rbloggers) May 15, 2021
How to find dataset differences in R Quickly Compare Datasets {https://t.co/tU2Bjh416q} #rstats #DataScience
— R-bloggers (@Rbloggers) May 25, 2021
GitHub With R {https://t.co/ZC5n2jnMAO} #rstats #DataScience
— R-bloggers (@Rbloggers) May 16, 2021
Principal component analysis (PCA) in R {https://t.co/68xX2eIANs} #rstats #DataScience
— R-bloggers (@Rbloggers) May 7, 2021
Build and improve a Machine Learning Classification model with TidyModels and R {https://t.co/lNBLmSpyHm} #rstats #DataScience
— R-bloggers (@Rbloggers) May 25, 2021
Power analysis in Statistics with R {https://t.co/0Efo5vrjdd} #rstats #DataScience
— R-bloggers (@Rbloggers) May 8, 2021
New features in R 4.1.0 {https://t.co/wmYN0OHixh} #rstats #DataScience
— R-bloggers (@Rbloggers) May 18, 2021
Awesome R Markdown Word report with programmatically inserted headings, outputs and… {https://t.co/5azjRGpeUv} #rstats #DataScience
— R-bloggers (@Rbloggers) May 15, 2021
Animated Graph GIF with gganimate & ggplot {https://t.co/MBYEaTYied} #rstats #DataScience
— R-bloggers (@Rbloggers) May 15, 2021
ggplot: the placing and order of aesthetics matters {https://t.co/Aeob9IPyTx} #rstats #DataScience
— R-bloggers (@Rbloggers) May 16, 2021
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```